Learning neural networks can be used to effectively classify large amounts of data and to reveal connections and groupings in measurements and large masses of data, which are very difficult to find using statistical analysis, mathematical models, or logical rules. International patent publication WO 01/75222 discloses a method, exploiting a neural network, for monitoring a paper production process and gives references to the general literature on neural networks. According to experience, the method disclosed by the publication can be used to reveal a process moving away from the optimal zone, well before problems appear in the form of, for example, a web break. The electrochemical measurements are preferably carried out using equipment according to publication WO 01/25774.
However, the use of the known method will not determine the cause of a problem very quickly, even if, when an index deviation occurs, the input variables of the neural network are examined. Often, the cause is not a matter of deviation in a single input variable, but rather of a detrimental combination of several variables. In addition, the known method regards a paper machine as being a totality, even though the production process is divided into clearly discernable sub-processes.